Jennifer L. Hofmann

DyAb predicts antibody properties and designs new sequences with high binding affinity using a low-data approach.

This paper introduces a machine learning framework for therapeutic antibody design that integrates computational methods with experimental validation, resulting in significantly improved binding affinity for multiple targets.

This study tracks ribosome-sized particles in E. coli to show that their 3D diffusion is influenced by macromolecular interactions and geometrical confinement, revealing sub-diffusive motion due to nucleoid and cell boundary constraints.